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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "MatrixQCvis" in publications use:'
type: software
license: GPL-3.0-only
title: 'MatrixQCvis: Shiny-based interactive data-quality exploration for omics data'
version: 1.13.5
doi: 10.32614/CRAN.package.MatrixQCvis
abstract: Data quality assessment is an integral part of preparatory data analysis
  to ensure sound biological information retrieval. We present here the MatrixQCvis
  package, which provides shiny-based interactive visualization of data quality metrics
  at the per-sample and per-feature level. It is broadly applicable to quantitative
  omics data types that come in matrix-like format (features x samples). It enables
  the detection of low-quality samples, drifts, outliers and batch effects in data
  sets. Visualizations include amongst others bar- and violin plots of the (count/intensity)
  values, mean vs standard deviation plots, MA plots, empirical cumulative distribution
  function (ECDF) plots, visualizations of the distances between samples, and multiple
  types of dimension reduction plots. Furthermore, MatrixQCvis allows for differential
  expression analysis based on the limma (moderated t-tests) and proDA (Wald tests)
  packages. MatrixQCvis builds upon the popular Bioconductor SummarizedExperiment
  S4 class and enables thus the facile integration into existing workflows. The package
  is especially tailored towards metabolomics and proteomics mass spectrometry data,
  but also allows to assess the data quality of other data types that can be represented
  in a SummarizedExperiment object.
authors:
- family-names: Naake
  given-names: Thomas
  email: thomasnaake@googlemail.com
  orcid: https://orcid.org/0000-0001-7917-5580
- family-names: Huber
  given-names: Wolfgang
  email: wolfgang.huber@embl.de
  orcid: https://orcid.org/0000-0002-0474-2218
repository: https://bioc.r-universe.dev
commit: 465423b5d146f5e7212c41a1837f14a42402326c
date-released: '2024-06-27'
contact:
- family-names: Naake
  given-names: Thomas
  email: thomasnaake@googlemail.com
  orcid: https://orcid.org/0000-0001-7917-5580